Python async driver takes same amount of time with sync driver

Drivers & Stacks
1

I'm using python async driver to import data to my Neo4j database. However, it is rather slow and when I test it with sync driver, I realized that it takes same amount of time to import data. It processes 120k rows in 1 hour with 8 threads. Here is the code I'm using:

async def run_cql(cql, dict):
    async with self._async_driver.session(**self.db_config) as session:
        await session.run(cql, dict=dict)

async import(htmls):
    for i, html in enumerate(htmls):
            print("Processing article %.2f%%" % (i * 100 / len(htmls))) if i % 100 == 0 else None
            rows.append(html)
            if len(rows) == self.chunk_size:
                chunk_num = chunk_num + 1
                session_index = (chunk_num - 1) % self.thread_count
                rows_dict = {'rows': rows}

                process_params.append({'session_index': session_index, 'cql': self.cql,
                                       'rows_dict': rows_dict})

                if session_index == self.thread_count - 1:
                    tasks = []
                    for p in process_params:
                        tasks.append(asyncio.create_task(
                            self.run_cql(p['cql'], p['rows_dict'])))

                    await asyncio.gather(*tasks)

                    process_params = []

                rows = []

Is there anything wrong with my code? Or is there any additional configuration that I should make on Neo4j side. I set thread worker count to 8, it didn't matter.